Mortality rates of coronavirus disease‐2019 (COVID‐19) continue to rise across the world. Information regarding the predictors of mortality in patients with COVID‐19 remains scarce. Herein, we ...performed a systematic review of published articles, from 1 January to 24 April 2020, to evaluate the risk factors associated with mortality in COVID‐19. Two investigators independently searched the articles and collected the data, in accordance with PRISMA guidelines. We looked for associations between mortality and patient characteristics, comorbidities, and laboratory abnormalities. A total of 14 studies documenting the outcomes of 4659 patients were included. The presence of comorbidities such as hypertension (odds ratio OR, 2.5; 95% confidence interval CI, 2.1‐3.1; P < .00001), coronary heart disease (OR, 3.8; 95% CI, 2.1‐6.9; P < .00001), and diabetes (OR, 2.0; 95% CI, 1.7‐2.3; P < .00001) were associated with significantly higher risk of death amongst patients with COVID‐19. Those who died, compared with those who survived, differed on multiple biomarkers on admission including elevated levels of cardiac troponin (+44.2 ng/L, 95% CI, 19.0‐69.4; P = .0006); C‐reactive protein (+66.3 µg/mL, 95% CI, 46.7‐85.9; P < .00001); interleukin‐6 (+4.6 ng/mL, 95% CI, 3.6‐5.6; P < .00001); D‐dimer (+4.6 µg/mL, 95% CI, 2.8‐6.4; P < .00001); creatinine (+15.3 µmol/L, 95% CI, 6.2‐24.3; P = .001); and alanine transaminase (+5.7 U/L, 95% CI, 2.6‐8.8; P = .0003); as well as decreased levels of albumin (−3.7 g/L, 95% CI, −5.3 to −2.1; P < .00001). Individuals with underlying cardiometabolic disease and that present with evidence for acute inflammation and end‐organ damage are at higher risk of mortality due to COVID‐19 infection and should be managed with greater intensity.
Highlights
This systematic review and meta‐analysis of 14 studies including a total of 4659 patients comprehensively identifies the risk factors associated with mortality in COVID‐19 included clinical comorbidities such as hypertension, coronary heart disease, and diabetes, as well as laboratory abnormalities including elevated levels of cardiac troponin, interleukin‐6, C‐reactive protein, D‐dimer and markers of liver and renal function.
Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant ...studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.
For many complex traits, gene regulation is likely to play a crucial mechanistic role. How the genetic architectures of complex traits vary between populations and subsequent effects on genetic ...prediction are not well understood, in part due to the historical paucity of GWAS in populations of non-European ancestry. We used data from the MESA (Multi-Ethnic Study of Atherosclerosis) cohort to characterize the genetic architecture of gene expression within and between diverse populations. Genotype and monocyte gene expression were available in individuals with African American (AFA, n = 233), Hispanic (HIS, n = 352), and European (CAU, n = 578) ancestry. We performed expression quantitative trait loci (eQTL) mapping in each population and show genetic correlation of gene expression depends on shared ancestry proportions. Using elastic net modeling with cross validation to optimize genotypic predictors of gene expression in each population, we show the genetic architecture of gene expression for most predictable genes is sparse. We found the best predicted gene in each population, TACSTD2 in AFA and CHURC1 in CAU and HIS, had similar prediction performance across populations with R2 > 0.8 in each population. However, we identified a subset of genes that are well-predicted in one population, but poorly predicted in another. We show these differences in predictive performance are due to allele frequency differences between populations. Using genotype weights trained in MESA to predict gene expression in independent populations showed that a training set with ancestry similar to the test set is better at predicting gene expression in test populations, demonstrating an urgent need for diverse population sampling in genomics. Our predictive models and performance statistics in diverse cohorts are made publicly available for use in transcriptome mapping methods at https://github.com/WheelerLab/DivPop.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Epigenetic clocks have been widely used to predict disease risk in multiple tissues or cells. Their success as a measure of biological ageing has prompted research on the connection between ...epigenetic pathways of ageing and the socioeconomic gradient in health and mortality. However, studies examining social correlates of epigenetic ageing have yielded inconsistent results. We conducted a comprehensive, comparative analysis of associations between various dimensions of socioeconomic status (SES) (education, income, wealth, occupation, neighbourhood environment, and childhood SES) and eight epigenetic clocks in two well-powered US ageing studies: The Multi-Ethnic Study of Atherosclerosis (MESA) (n = 1,211) and the Health and Retirement Study (HRS) (n = 4,018). In both studies, we found robust associations between SES measures in adulthood and the GrimAge and DunedinPoAm clocks (Bonferroni-corrected p-value < 0.01). In the HRS, significant associations with the Levine and Yang clocks were also evident. These associations were only partially mediated by smoking, alcohol consumption, and obesity, which suggests that differences in health behaviours alone cannot explain the SES gradient in epigenetic ageing in older adults. Further analyses revealed concurrent associations between polygenic risk for accelerated intrinsic epigenetic ageing, SES, and the Levine clock, indicating that genetic risk and social disadvantage may contribute additively to faster biological aging.
For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key ...public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer's disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer's disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer's disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
IMPORTANCE: Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have ...directly compared these markers in the same cohorts. OBJECTIVE: To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor–based model. DESIGN, SETTING, AND PARTICIPANTS: Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands. EXPOSURE: Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations PCEs), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score. MAIN OUTCOMES AND MEASURES: Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed. RESULTS: The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, −0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years). CONCLUSIONS AND RELEVANCE: In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors.
As a nonmutagenic human carcinogen, arsenic (As)'s carcinogenic activity is likely the result of epigenetic changes, particularly alterations in DNA methylation. While increasing studies indicate a ...potentially important role for timing of As exposure on DNA methylation patterns and the subsequent differential risks for As toxicity and carcinogenesis, there is a lack of research that tackles these critical questions, particularly in human based populations. Here we reported a family-based study including three generations, in which each generation living in the same household had a distinctive timing of As exposure: in adulthood, in utero and during early childhood, and in germlines exposure for grandparents, parents, and grandchildren, respectively. We generated genome-wide DNA methylation data for 18 As-exposed families, nine control families, as well as 18 arsenical skin lesion patients. Our analysis showed that As exposure may leave detectable DNA methylation changes even though exposure occurred decades ago, and the most significant changes of global DNA methylation were observed among patients afflicted with arsenical skin lesions. As exposure across generations shared common differentially methylated DNA loci and regions (744 DML and 15 DMRs) despite the distinctive exposure timing in each generation. Importantly, based on these DML, clustering analysis grouped skin lesion patients together with grandparents in exposed families in the same cluster, separated from grandparents in control families. Further analysis identified a number of DML and several molecular pathways that were significantly distinguished between controls, exposed populations, as well as skin lesion patients. Finally, our exploratory analysis suggested that some of these DML altered by As exposure, may have the potential to be inherited affecting not only those directly exposed but also later generations. Together, our results suggest that common DML and/or DMRs associated with an increased risk for disease development could be identified regardless of when exposure to As occurred during their life span, and thus may be able to serve as biomarkers for identifying individuals at risk for As-induced skin lesions and possible cancers.
•Historical arsenic exposure could leave detectable DNA methylation changes.•Arsenic exposure induces common DNA methylation changes across multiple generations.•Aberrant DNA methylations are enriched in patients with arsenic-induced skin lesions.•Potential for the transgenerational epigenetic impact of arsenic exposure is explored.
Obesity promotes systemic insulin resistance through inflammatory changes that lead to the release of cytokines from activated macrophages. Although the mechanism is unclear, the second messenger ...cAMP has been found to attenuate macrophage activity in response to a variety of hormonal signals. We show that, in the setting of acute overnutrition, leptin triggers catecholamine-dependent increases in cAMP signaling that reduce inflammatory gene expression via the activation of the histone deacetylase HDAC4. cAMP stimulates HDAC4 activity through the PKA-dependent inhibition of the salt-inducible kinases (SIKs), which otherwise phosphorylate and sequester HDAC4 in the cytoplasm. Following its dephosphorylation, HDAC4 shuttles to the nucleus where it inhibits NF-κB activity over proinflammatory genes. As variants in the Hdac4 gene are associated with obesity in humans, our results indicate that the cAMP-HDAC4 pathway functions importantly in maintaining insulin sensitivity and energy balance via its effects on the innate immune system.
Display omitted
•Leptin stimulates increases in cAMP signaling in adipose tissue macrophages•cAMP inhibits NF-κB activity via activation of class IIa HDACs•Snps in the Hdac4 gene are associated with human obesity•Macrophage HDAC4 mediates anti-inflammatory effects of catecholamines in adipose
Luan et al. show that increases in sympathetic nerve activity mediated by leptin in response to overnutrition trigger the activation of cAMP-responsive pathways that reduce the expression of inflammatory cytokines via the activation of the histone deacetylase HDAC4. Variants in the Hdac4 gene are also associated with obesity in humans.
The pathogenesis of polycystic ovary syndrome (PCOS) is poorly understood. PCOS-like phenotypes are produced by prenatal androgenization (PA) of female rhesus monkeys. We hypothesize that ...perturbation of the epigenome, through altered DNA methylation, is one of the mechanisms whereby PA reprograms monkeys to develop PCOS. Infant and adult visceral adipose tissues (VAT) harvested from 15 PA and 10 control monkeys were studied. Bisulfite treated samples were subjected to genome-wide CpG methylation analysis, designed to simultaneously measure methylation levels at 27,578 CpG sites. Analysis was carried out using Bayesian Classification with Singular Value Decomposition (BCSVD), testing all probes simultaneously in a single test. Stringent criteria were then applied to filter out invalid probes due to sequence dissimilarities between human probes and monkey DNA, and then mapped to the rhesus genome. This yielded differentially methylated loci between PA and control monkeys, 163 in infant VAT, and 325 in adult VAT (BCSVD P<0.05). Among these two sets of genes, we identified several significant pathways, including the antiproliferative role of TOB in T cell signaling and transforming growth factor-β (TGF-β) signaling. Our results suggest PA may modify DNA methylation patterns in both infant and adult VAT. This pilot study suggests that excess fetal androgen exposure in female nonhuman primates may predispose to PCOS via alteration of the epigenome, providing a novel avenue to understand PCOS in humans.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Objective
Aging is associated with impaired insulin sensitivity and increased prevalence of type 2 diabetes. However, it remains unclear whether aging‐associated insulin resistance is due to ...increased adiposity or other age‐related factors. To address this question, the impact of aging on insulin sensitivity was investigated independently of changes in body composition.
Methods
Cohorts of mice aged 4 to 8 months (“young”) and 18 to 27 months (“aged”) exhibiting similar body composition were characterized for glucose metabolism on chow and high‐fat diets. Insulin sensitivity was assessed by hyperinsulinemic‐euglycemic clamp analyses. The relationship between aging and insulin resistance in humans was investigated in 1,250 nondiabetic Mexican Americans who underwent hyperinsulinemic‐euglycemic clamps.
Results
In mice with similar body composition, age had no detrimental effect on plasma glucose and insulin levels. While aging did not diminish glucose tolerance, hyperinsulinemic‐euglycemic clamps demonstrated impaired insulin sensitivity and reduced insulin clearance in aged mice on chow and high‐fat diets. Consistent with results in the mouse, age remained an independent determinant of insulin resistance after adjustment for body composition in Mexican American males.
Conclusions
This study demonstrates that in addition to altered body composition, adiposity‐independent mechanisms also contribute to aging‐associated insulin resistance in mice and humans.
PDF
